With the advent of the digital times, presentation of both music and video has transformed from analog signals to digital signals. This transformation has not only enriched the applications of music and video, but has also increased the added value of many electronic products. For example, conventional analog monitors are simply able to capture videos for the purpose of monitoring by a user. However, as a result of digitalization, most of these monitors currently available in the market may be used with a computing device (e.g., a personal computer (PC) or a System on Chip (SOC) device) so that the computing device may apply video images captured by the monitor in real time, thereby increasing the added value of the device remarkably.
To accomplish real-time detection of an object in video images successfully, object detection methods conventionally used can be summarized as follows:                (1) an application of a stable target object is searched for by identifying changes of scenes in video images, and several adjacent images are calculated and processed as a basic processing approach of this method;        (2) a 3D realistic object is established by transforming 2D images captured by multiple image capturing devices at different angles and detecting pixel values of a same object in the 2D frames respectively to improve the accuracy of the object detection; and        (3) bit planes of pixels in two consecutive images are compared directly or by detecting a motion vector thereof to accomplish the purpose of real-time anti-shaking detection of the images.        
However, the object detection method (1) has to make calculations on at least several adjacent images, which consumes considerable time in calculation and increases the computational complexity; the object detection method (2) may improve the accuracy of object detection by establishing a 3D realistic object, but it also suffers from a considerably increased computational complexity; and the object detection method (3) is able to perform real-time anti-shaking processing on images, but it has no consideration of the reliability of local motion vector (LMV) in the block.
Accordingly, it is highly desirable in the art to provide a solution for detecting an object in video images in real time without compromising the detection accuracy and computational complexity.